Controller Performance Assessment (CPA) of Intelligent Control for Non-linear System

Abstract

The objective of this paper is to design and undertake comparative analysis of classical and intelligent controllers for nonlinear system. These controllers are compared based on controller performance assessment in which the different parameters as overshoot, steady-state error, rise time, settling time, response of reference change and output variance are analyzed. To achieve these objectives, the water tank control problem as nonlinear system has been built in Simulink and implementations traditionally classical controller and advance intelligent controller as fuzzy logic and neural network are performed. In classical controller, the proposal-integral control law is used as control algorithm. Sugeno model is used for FL controller, while back propagation algorithm is used to train the NARMA-l2 neural network control. Three controllers are designed and their performances are compared.

Keywords: Controller performance assessment (CPA), classical controller, fuzzy logic controller, NARMA-l2 neural controller, nonlinear system